Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/74289
Título: Automatic satellite image georeferencing using a contour-matching approach
Autores/as: Eugenio, Francisco 
Marqués, Ferran
Clasificación UNESCO: 332401 Satélites artificiales
3301 Ingeniería y tecnología aeronáuticas
Palabras clave: Image Georeferencing
Multitemporal and Multisensor Images
Remote Sensing Image Processing
Fecha de publicación: 2003
Publicación seriada: IEEE Transactions on Geoscience and Remote Sensing 
Resumen: Multitemporal and multisatellite studies or comparisons between satellite data and local ground measurements require nowadays precise and automatic geometric correction of satellite images. This paper presents a fully automatic geometric correction system capable of georeferencing satellite images with high accuracy. An orbital prediction model, which provides initial earth locations, is combined with the proposed automatic contour-matching technique. This combination allows correcting the low-frequency error component, mainly due to timing and orbital model errors, as well as the high-frequency error component, due to variations in the spacecraft's attitude. The approach aims at exploiting the maximum reliable information in the image to guide the matching algorithm. The contour-matching process has three main steps: 1) estimation of the gradient energy map (edges) and detection of the cloudless (reliable) areas; 2) initialization of the contours positions; 3) estimation of the transformation parameters (affine model) using a contour optimization approach. Three different robust and automatic algorithms are proposed for optimization, and their main features are discussed. Finally, the performance of the three proposed algorithms is assessed using a new error estimation technique applied to Advanced Very High Resolution Radiometer (AVHRR), Sea-viewing Wide Field ofview Sensor (SeaWiFS), and multisensor AVHRR-SeaWiFS imagery.
URI: http://hdl.handle.net/10553/74289
ISSN: 0196-2892
DOI: 10.1109/TGRS.2003.817226
Fuente: IEEE Transactions on Geoscience and Remote Sensing [ISSN 0196-2892], v. 41 (12), p. 2869-2880, (Diciembre 2003)
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